Introduction Asthma remains a major global health burden, particularly in contexts of poor air quality where managing moderate and severe diagnosis ideally requires continuous, coordinated care and remote monitoring beyond episodic clinic visits. In this setting, this early feasibility study evaluates a novel digital health platform, developed as part of an integrative eHealth Monitoring Ecosystem for patients diagnosed with moderate or severe asthma, aimed at supporting personalised, continuous asthma care through remote physiological and air quality monitoring. Methods The system was conceptualized, designed, refined, and assessed throughout the study, integrating wearable physiological sensors, individualised portable air quality monitors, and a digital interface with separate portals for patients and clinicians. Thirteen patients and seven clinicians participated in a six-month pilot, interacting with the platform through their respective user interfaces. Their views on system use, care processes, emotional responses, overall satisfaction, and the anticipated integration of the system into routine care were assessed using a 26-item Likert-scale Patient-Reported Experience Measures (PREMs) questionnaire, administered to both patients and clinicians and organized into five domains: user experience (including both patients and clinicians), patient experience, emotional experience, overall satisfaction, and future implementation expectations. An additional open-ended comment (item 27) was included and analyzed using inductive qualitative methods in NVivo, with themes aligned to the same five clusters. Results The findings indicate a high level of positive experience with the eHealth Monitoring Ecosystem across all PREMs domains, with patients requesting more clinical and technical information and clinicians identifying the need for enhanced functionality and additional tools. Conclusion These results support the feasibility and acceptability of the eHealth Monitoring Ecosystem for moderate and severe asthma management and suggest directions for further refinement, broader clinical evaluation, and potential adaptation to other chronic disease monitoring contexts.
Escalona-López et al. (Wed,) studied this question.